The present invention relates in general to maintenance and risk assessment systems and, in particular, to a method and apparatus for measuring one or more vehicle operating parameters based on actual vehicle use, and for accumulating and processing such information to yield critical automobile warranty statistical data.
Maintenance and risk assessment systems are used in a variety of business and other private and public contexts. Generally, an important objective of such systems is to analyze certain activities based on identifiable correlations between selected variables and related maintenance and risk factors. Such correlations can be useful in scheduling maintenance and assessing the risk associated with the activity under consideration so that a determination can be made, for example, as to whether to undertake/allow the activity and/or how to allocate the risk such as through risk-based pricing or establishment of appropriate warranty terms.
The case of the automobile warranty business is illustrative. Warranties are often provided, for example, in connection with automobile purchases. Indeed, the availability of such warranties, and the resulting certainty in overall vehicle use costs, is a significant factor for inducing some consumers to purchase an automobile. In this regard, the warranty may specify that a manufacturer, an underwriter, or some other related party will pay to repair or replace the vehicle under certain circumstances. Such warranties obviously increase costs to the warrantor and this increased cost is generally ultimately reflected in purchase prices, as a separate pricing item or otherwise. Accordingly, both the warrantor and purchaser have an interest in reducing vehicle wear costs and in monitoring the costs.
In order for the contract prices to reflect true operating expenses, as may be considered most equitable or sensible, it is desirable to accurately assess the risk associated with a given contract or type of contract. To this end, the warranty cost may be determined by identifying variables associated with a particular contract that correlate to particular risk factors. In the automobile warranty business, examples of such variables include: the make and model of the vehicle, the climate and terrain in which the vehicle is used, the driving habits of the vehicle drivers, etc. Examples of risk factors include the frequency and cost for repair/replacement associated with particular types of damage. Thus, for example, a contract price for a particular class of vehicle having higher historical repair costs may reflect such higher costs as a warranty item or otherwise. Similarly, vehicles may be scheduled for more or less frequent maintenance depending on climate or driving conditions.
Conventionally, the process for identifying such variable/risk factor correlations involves postulating such a correlation, obtaining data relating to the relevant variable and risk factor, and analyzing the data to confirm, quantify and/or refute the postulation. The initial step of postulating a correlation is often based on the professional experience of an analyst. Postulations are often based on anecdotal information or third party studies, e.g. Consumer Reports studies for a particular make and model of vehicle. Based on such a postulation, the analyst may acquire data, for example, by accessing a database of archived records for relevant car vehicles and claims. This data may then be provided to a computer system programmed to execute conventional risk analysis routines. The computer system can then conduct an analysis and provide an output that the analyst can use to confirm, quantify or refute the postulation.
It will be appreciated that there are significant limitations on the types of analyses that can be conducted based on archived claim records. In particular, such records generally provide useful aggregated information for trending analysis and the like, but generally provide little or no data correlating specific vehicle usage patterns to associated claims.
It is therefore desirable to measure and accumulate operating parameter information based on vehicle usage and for analyzing the resulting information to yield critical automobile warranty statistical data. The present invention provides valuable information regarding vehicle usage patterns that can improve risk assessment and allow for improved warranty contract management.
In accordance with one aspect of the present invention, an apparatus is provided for use in monitoring one or more operating parameters related to vehicle wear. The apparatus includes a support structure such as a frame or housing for interconnection to the vehicle such that the support structure is carried by the vehicle during operating, and a sensor for monitoring a first operating parameter and providing a sensor signal indicative of the first operating parameter. The support structure can be attached to an interior or exterior portion of the vehicle. The sensor may sense any of various parameters such as a current (e.g., related to operation of a brake light, a starter solenoid, an air conditioner clutch or headlight), a thermal value, (e.g., heat related to air entering a radiator, or heat related to operation of an engine, air conditioner compressor or air condition condenser), an acceleration value (e.g., related to a forward or braking acceleration, a vertical component of acceleration or side-to-side acceleration) or an induction related value (e.g., an inductance related to operation of a spark plug). The support structure carries a processor for receiving information based on the sensor signal and for processing the information to generate processed information. The apparatus further includes a memory structure associated with the processor for storing the processed information, a first interface structure for interfacing the memory structure with the processor and a second interface structure for use in accessing the processor so as to retrieve the processed information from the memory structure for use by an external processing system. The second interface may include, for example, an output port for use in downloading the processed information or a data port for interfacing with a wireless communications device, for example, a cordless telephone.
In accordance with another aspect of the present invention, multiple operating parameters are monitored to obtain composite parameter information. It has been recognized that certain vehicle wear characteristics can be more meaningfully monitored by concurrently tracking combinations of operating parameters. For example, to analyze brake wear, it may be useful to monitor a brake application event in conjunction with a duration of the event and/or an operating speed of the vehicle. The associated process includes the steps of: mounting an electronics unit on a vehicle, where the electronics unit includes a first sensor for monitoring a first operating parameter and a second sensor for monitoring a second operating parameter; monitoring the first parameter during a first time period to obtain first parameter information; monitoring the second parameter during the second time period to obtain second parameter information where the first and second time periods overlap; and analyzing the first parameter information in conjunction with the second parameter information to obtain automobile warranty statistical data. In this manner, multivariate analyses can be performed to improve warranty data.
According to another aspect of the present invention, a method is provided for analyzing monitored operating parameter information to obtain warranty statistical data. The method involves downloading parameter information from a database including operating parameter information obtained by monitoring one or more operating parameters during vehicle use and applying a statistical tool to the operating parameter information to derive a mathematical model for characterizing the parameter information. The mathematical model may comprise, for example, a repairable system model. The method may further include the step of comparing the resulting mathematical model to empirical data to confirm the predictive quality of the model.